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focused on modeling and simulations of turbulent mixed-phase clouds. This interdisciplinary project encourages collaboration with experts in atmospheric physics. The successful candidate will contribute
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degree obtained within the last three years prior to the application deadline. What you will do Develop hybrid quantum–classical methods to improve simulation and prediction of multiphase reactors. Design
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, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty and
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design. One of our group's goals is to create efficient surrogate models that reduce the computational cost of MD simulations by several orders of magnitude. Notable examples of our work in this area
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, components, overall system performance) Numerical methods and simulation tools (e.g., Python/Matlab, CFD modelling, optimization) Beyond technical skills, we value people who contribute to a healthy and
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experimental, pilot-scale, or high-fidelity simulation data into model calibration and validation workflows Design and run numerical simulations of multiphase flow systems and reactors Quantify model uncertainty
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to work on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal we have a variety of projects related to: Simulation, design and
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cost of MD simulations by several orders of magnitude. Notable examples of our work in this area include Boltzmann Generators [1 ,2 ], Surrogate-model Assisted Molecular Dynamics [3 ], and Implicit
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forms suitable for system-level reasoning, and ensuring consistency between detailed simulations, experimental data, and higher-level system models. The researcher is expected to contribute
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of variation simulation and digital twins. About us The Department of Industrial and Materials Science shares knowledge and their vision of technical solutions for the future industry in a sustainable society